The study enrolled 60 first-year medical students at a university in Ecuador who had completed the relevant functional anatomy course content. Their median age was 18 years, with an interquartile range of 18–19, and 51.7% of the participants were female. Researchers used a single-group pre-test–post-test design without a concurrent control group.

The same 35-item, single-best-answer multiple-choice test was administered immediately before and after students played the educational game. Questions were mapped to five Bloom’s taxonomy domains: remember, understand, apply, analyze and evaluate. Pre–post comparisons were performed with the Wilcoxon signed-rank test.

The most clearly measured change involved foundational cognitive domains. Median scores increased significantly in the “remember” and “understand” categories, indicating that students performed better on the test items designed to assess recall and comprehension immediately after gameplay. By contrast, the study found no statistically significant changes in the “apply,” “analyze” or “evaluate” domains.

The overall median Bloom score increased modestly from 21, with an interquartile range of 17–25, before the game to 22, with an interquartile range of 18.25–26, afterward. These findings distinguish the game’s immediate association with recall and understanding from the absence of a detected change in applying, analyzing or evaluating functional anatomy information. They also do not establish whether any additional knowledge was retained after the session.

An embedded qualitative strand examined learners’ experiences and their perceptions of the activity. After the intervention, students completed a five-point Likert-scale questionnaire adapted from the Technology Acceptance Model, and their perception scores were favorable. Six focus groups—three conducted before the intervention and three afterward—were analyzed using the Framework Method.

Participants identified immediate corrective feedback, repeated questioning, psychological safety and peer interaction as perceived mechanisms supporting learning. These are explanations offered by students rather than mechanisms directly demonstrated by the study. The design can document what learners believed was useful and how they experienced the activity, but the perceptions do not independently establish why test scores changed or whether the game would produce the same outcomes under different conditions.

The qualitative findings also identified potential downsides. Time pressure and competition were reported as stressors, showing that card-based learning could be perceived as both educational and uncomfortable. The study therefore examined test performance alongside students’ experiences rather than treating a favorable questionnaire response as evidence of educational efficacy.

The authors described the game as a potentially useful low-cost, low-stakes strategy for reinforcing functional anatomy after foundational teaching. That interpretation is consistent with the intervention’s placement and the measured pattern: students played after completing the relevant course material, and the significant gains were confined to remembering and understanding. Further controlled research would be needed to determine whether the immediate score difference is attributable to the game and whether its educational value extends beyond the immediate post-test.

Subject of Research: Mixed-methods evaluation of a card-based functional anatomy activity for first-year medical students

Article Title: Can a card-based educational game enhance functional anatomy knowledge in first-year medical students? A mixed-methods study

Article References: Villacrés Villegas, J., Villegas Villao, N., Arreaga-Yulan, A. R., Briones-Zamora, A. D., Gálvez López, A. A., Briones-Claudett, K. H., & Briones-Zamora, K. H. (2026). Can a card-based educational game enhance functional anatomy knowledge in first-year medical students? A mixed-methods study. BMC Medical Education. https://doi.org/10.1186/s12909-026-10386-5

Image Credits: AI Generated

DOI: 10.1186/s12909-026-10386-5

Keywords: medical education, functional anatomy, card-based learning, first-year medical students, game-based learning, pre-test–post-test study, Bloom’s taxonomy, focus groups, knowledge retention, student perceptions, card-based, educational

The research team, led by Zainab Al Kindi of the Department of Community and Mental Health Nursing, set out to address a persistent gap in nursing education. Global health challenges, including emerging infections, population mobility, climate-related health risks, noncommunicable diseases, and health inequities, increasingly shape day-to-day nursing practice. Yet evidence on whether structured, curriculum-embedded courses actually improve students’ perceived competency has remained limited, particularly in countries where global health education is still maturing within undergraduate nursing curricula.

To measure the effect, the researchers used a one-group pre-test–post-test design, one of the most direct ways to evaluate change within a cohort. Each of the eighty participating students completed a questionnaire before the course began and again after finishing it. The measurement instrument was a course-aligned adaptation informed by the Global Health Competencies for Nurses framework, covering seven distinct domains: global burden of disease, global health priorities, social and environmental determinants of health, professional practice, health equity and social justice, programme management, and economic, sociocultural, and political awareness.

The headline result was unambiguous. Overall perceived global health competency rose from a mean of 2.46 on the pre-test, with a standard deviation of 0.81, to a mean of 3.08 on the post-test, with a standard deviation of 0.44. That represents a mean increase of 0.62 points, with a 95 percent confidence interval of 0.40 to 0.84. The paired-samples t test yielded t(79) = 5.62 and p < .001, while the paired-samples effect size, Cohen’s dz, came in at 0.63, a medium-to-large effect by conventional standards. Notably, the drop in standard deviation from 0.81 to 0.44 suggests the course did not merely lift the average; it also narrowed the spread between students, bringing lower-scoring students closer to their peers.

The improvement was not confined to a single dimension of competency. Students showed significant gains across all seven domains of the adapted scale. The largest single improvement appeared in health equity and social justice, where the mean increased by 0.90 points, with a 95 percent confidence interval of 0.68 to 1.12, t(79) = 8.14, p < .001, and a Cohen’s dz of 0.91. An effect size approaching 1.0 in a paired design indicates that, for the average student, the shift in perceived understanding of equity and justice was substantial, not a marginal statistical artifact.

Why would equity and social justice show the steepest climb? The authors’ framework places these concepts at the heart of global health thinking, and they are often the least familiar territory for students entering nursing school. Concepts such as the social determinants of health, structural inequities, and the uneven distribution of disease burden across populations require a conceptual reframing that clinical training alone rarely provides. A dedicated course gives students the vocabulary, evidence base, and analytical tools to see health outcomes as products of social, economic, and political arrangements, not just individual biology or behavior. The data suggest that once that reframing occurs, students recognize it themselves in their self-assessed competency.

The study also uncovered an interesting baseline pattern. Students who had previously participated in global health activities, such as exchanges, volunteer work, or related extracurricular engagement, reported higher competency before the course even began. This aligns with a broader principle in competency development: prior exposure builds familiarity and confidence. However, by the post-test, competency scores did not differ significantly across participant characteristics. In other words, the course appears to have leveled the field, giving students without prior global health exposure the same measurable boost that brought them up to par with their more experienced classmates.

Methodologically, the one-group pre-test–post-test design has known limitations that the findings should be read against. Without a control group, it is impossible to fully rule out alternative explanations such as maturation, concurrent coursework, or test-retest effects. Self-reported perceived competency also measures confidence and self-assessment rather than directly observed skill. Nevertheless, the design is well suited to course evaluation, and the consistency of improvement across all seven domains, combined with conventional statistical rigor including confidence intervals and paired effect sizes, strengthens the case that the course itself drove the change. The study received ethical approval from the Research and Ethics Committee of the College of Nursing at Sultan Qaboos University and was conducted in accordance with the Declaration of Helsinki, with data collection handled by someone not involved in teaching or assessment to reduce pressure on students.

The implications extend beyond one university in Muscat. The authors argue that integrating global health education within undergraduate nursing curricula offers a scalable approach to preparing future nurses for equity-oriented, culturally responsive, and globally informed practice. Because the course was embedded in the existing curriculum rather than offered as an optional add-on, the model does not require students to find extra time or resources, making it attractive for nursing schools in low- and middle-income countries and beyond. As climate change alters disease patterns and populations grow more mobile, the demand for nurses who understand global health dynamics will only intensify.

There is also a broader policy dimension. The researchers note that strengthening perceived global health competency in nursing education may support progress toward the United Nations Sustainable Development Goals related to health and quality education. A workforce of nurses who grasp the global burden of disease, the economics of health systems, and the politics of health inequity is better positioned to deliver care that closes gaps rather than widening them. For a profession that makes up the largest share of the global health workforce, that shift in perspective, achieved in a single course, may prove to be one of the most cost-effective investments in health equity available to educators today.

Subject of Research: The effect of a structured global health course on perceived global health competency in undergraduate nursing students

Article Title: Enhancing perceived global health competency among undergraduate nursing students: a pre-test–post-test course evaluation

Article References: Kindi, Z. A., Yahyaei, A. A., Joseph, M., & Sabei, S. A. (2026). Enhancing perceived global health competency among undergraduate nursing students: a pre-test–post-test course evaluation. BMC Nursing. https://doi.org/10.1186/s12912-026-05412-2

Image Credits: AI Generated

DOI: 10.1186/s12912-026-05412-2

Keywords: global health competency, nursing education, undergraduate nursing students, curriculum evaluation, health equity, pre-test post-test study, social determinants of health, Sultan Qaboos University, BMC Nursing, nursing workforce, culturally responsive care, sustainable development goals

The research team, led by Maria Dolores Vivas-Urias, Cristina Obispo-Diaz, and Maria Auxiliadora Ruiz-Rosillo, tracked 180 university teachers across two consecutive academic years, 2023–2024 and 2024–2025, using a pre-experimental one-group pre-test and post-test design. Rather than comparing trained teachers against an untrained control group, the study measured the same cohort twice: once before and once after the rollout of the university’s GenAI Institutional Plan 2023–2025. This design allowed the researchers to capture within-person change on three core dimensions: general awareness of generative AI, beliefs about its impact on professions, and the perceived importance of learning AI tools for integration into student training.

The headline result is striking in its magnitude. Teachers’ self-reported awareness of generative AI rose by an average of 2.24 points on a ten-point scale, climbing from 4.82 to 7.06, a difference the authors characterize as clear and statistically significant. Perceptions followed a parallel trajectory. By the second year, 80.9 percent of surveyed teachers believed generative AI would transform the way they teach, an increase of 3.76 percentage points. Belief in the technology’s impact on students’ professional futures also rose, with the overall mean score increasing from 7.97 to 8.67 out of 10. Perhaps most tellingly for institutional planners, the perceived importance of learning AI tools for integration into student training reached 8.63 in 2024–2025, a statistically significant gain of 0.56 points over the previous year.

Beneath these averages lies a structural insight that may prove the study’s most consequential contribution: awareness, perceived professional impact, and the motivation to learn form an interlocking psychological chain. Correlation analysis revealed a strong positive relationship of r = 0.718 between teachers’ perceptions of generative AI’s impact on students’ professional futures and the importance they attached to learning AI tools. A more moderate correlation of r = 0.316 linked overall AI awareness to perceived professional impact. In practical terms, teachers who understand the technology better are more convinced it will reshape their fields, and that conviction drives their appetite for training. The authors interpret this through established frameworks such as the Technology Acceptance Model, in which performance expectations, the belief that adopting a technology improves outcomes, fuel adoption.

The institutional machinery behind these shifts deserves scrutiny. UAX launched its GenAI Institutional Plan in the 2023–2024 academic year, establishing milestones for both short- and medium-term transformation. The centerpiece for faculty was a compulsory training program, the Level II Teaching Certification in Generative Artificial Intelligence, deliberately aligned with UNESCO’s AI Competency Framework for Teachers across its five dimensions: a human-centred mindset, ethics of AI, AI foundations and applications, AI for professional learning, and AI pedagogy. The certification combined asynchronous online micro-courses introducing fundamentals, ethical use, data privacy, and academic integrity with face-to-face or synchronous workshops in which teachers practiced prompt design, generated learning activities mapped to Bloom’s Taxonomy, and built assessment strategies and personalized educational materials.

Participation figures point to genuine appetite rather than mere compliance. Of 1,300 invited teachers, 65 percent engaged in at least one training activity, and 428 completed the full certification. Satisfaction ratings were high across the board: the certification scored 8.6 for course level and 8.5 for usefulness for professional development, while the shorter two-hour practical workshops scored even higher, reaching 9.1 and 9.2 on usefulness and recommendation respectively. Notably, 72 percent of participants reported they had been able to apply what they learned in their personal and professional lives, and the training’s culminating activity required each teacher to submit a concrete proposal for integrating AI into their own teaching practice. That contrasts with prior research in which educators reported strong general technology training yet still felt unprepared to work generative AI into their classrooms.

Behavioral indicators tracked alongside perceptions tell a consistent story. The share of teachers reporting no use of AI tools collapsed from 54.38 percent in 2023–2024 to 10.42 percent a year later, and use of AI for teaching purposes jumped from 16.59 percent to 43.40 percent of responses. ChatGPT remained the dominant tool, cited by 89.14 percent of users in 2024–2025, but Copilot usage rose sharply, from 7.57 percent of responses to 28.99 percent, likely aided by the institution’s provision of Microsoft Copilot through university Office 365 accounts. Nearly half of the sample, 45.73 percent, used both tools concurrently. Because 72.6 percent of participating teachers held part-time contracts and worked outside the university, the faster uptake in teaching contexts relative to professional practice suggests that institutional training, rather than external professional exposure, was the decisive accelerant.

The study is candid about its constraints. The absence of a control group means the changes cannot be causally attributed to the training program alone; broader cultural momentum around generative AI between 2023 and 2025 undoubtedly contributed. The voluntary response rate was low, at 16.6 percent of the overlapping faculty population, raising the possibility of self-selection bias in which the most motivated teachers dominated the sample. The measurement instrument itself, a three-item one-dimensional perception scale, showed acceptable reliability with a Cronbach’s alpha of 0.72 and omega of 0.76, but the authors acknowledge that the saturated factor model limits interpretive weight of the confirmatory fit indices, and the modest Kaiser–Meyer–Olkin value of 0.59 indicates restricted factorability that future work should address. Reliance solely on teacher self-report, without observational evidence of changed classroom practice, further narrows what the data can establish.

Qualitative responses flesh out where teachers want to go next. An inductive thematic analysis of open-ended answers from 67 respondents identified seven broad categories and 29 specific training needs, clustered around pedagogical integration of generative AI, personalized content creation, automated assessment, ethics and responsible use, contextualized technical development, and certified continuing education. The authors note that most of these demands map onto the existing certification program, but more technical requests, such as discipline-specific tool development, will require specialized professional development beyond the current generalist offer. Faculties of Education Sciences and Technology and Business led awareness scores in both years, while significant pre-post gains appeared across Healthcare Sciences, Medicine, Dentistry, and Veterinary Medicine, indicating that the training effect penetrated fields far removed from computer science.

For the global higher education sector, the study offers a rare data point in a debate dominated by policy documents rather than measured outcomes. Recent international analyses have catalogued how universities are issuing guidelines, redesigning assessment, and drafting ethical codes, but few have quantified how such institutional efforts move the people on the front lines. The UAX results support a systemic, ethical, and sustainable strategy in which AI literacy is treated as an ongoing faculty competency rather than a one-off compliance exercise, and in which generative AI is embedded directly into curricula to close the gap between university education and labor market demands. The authors recommend that future research measure the transfer of training into actual teaching practice, incorporate student perspectives, and complement self-report with behavioral evidence. If replicated with stronger designs, the core message, that well-structured institutional training can convert teacher anxiety about AI into informed professional momentum, could reshape how universities worldwide approach the fastest-moving educational transformation of the decade.

Subject of Research: University teachers' perceptions of generative artificial intelligence following an institutional training plan in higher education

Article Title: Analysis of teachers’ perceptions of the impact of Generative Artificial Intelligence in higher education

Article References: Vivas-Urias, M. D., Obispo-Díaz, C., & Ruiz-Rosillo, M. A. (2026). Analysis of teachers’ perceptions of the impact of Generative Artificial Intelligence in higher education. Journal of New Approaches in Educational Research, 15(1), Article 12. https://doi.org/10.1007/s44322-026-00060-5

Image Credits: AI Generated

DOI: 10.1007/s44322-026-00060-5

Keywords: generative artificial intelligence, higher education, teacher training, AI literacy, faculty perceptions, institutional policy, UNESCO AI competency framework, ChatGPT, educational innovation, pre-test post-test study, teacher professional development, Spain